Purpose Recent research has identified a relationship between perceived stress and problematic smartphone usage. However, little is known about the underlying mediating and moderating mechanisms. The present study aimed to test the relationship between perceived stress and problematic smartphone usage as well as the mediating role of online social support and the moderating role of perceived social support among Chinese undergraduates. Patients and Methods A sample of 1123 college students participated in the study. The Perceived Stress Scale, Mobile Phone Addiction Index Scale, Online Social Support Questionnaire, and Perceived Social Support Scale were used. Results Perceived stress was significantly and positively associated with problematic smartphone usage, and online social support partially mediated the relationship between perceived stress and problematic smartphone usage. Moderated mediation analysis suggested that perceived social support moderated the association between perceived stress and online social support. This relationship became stronger for college students with lower levels of perceived social support. Conclusion The results of this study can contribute to a better understanding of how perceived stress increases the risk of problematic smartphone usage. The importance of reducing online social support and enhancing perceived social support in preventing undergraduates’ problematic smartphone usage is highlighted. The findings should be taken with caution given the convenience sampling and cross-sectional study design.

Background and Aims: This three-wave longitudinal study investigated the effects of stressful life events on problematic smartphone use and the mediating roles of mental health problems (i.e., depressive symptoms, poor sleep quality, and suicidal ideation) in Chinese undergraduate students.Methods: A total of 197 undergraduate students completed the three-wave surveys. Their severity of stressful life events, mental health problems, and problematic smartphone use were assessed.Results: Regression analyses revealed that stressful life events at T1 was significantly associated with problematic smartphone use at T3. Mediation analyses showed that mental health problems (i.e., depressive symptoms, poor sleep quality, and suicidal ideation) at T2 fully mediated the association between stressful life events at T1 and problematic smartphone use at T3 (B = 0.042, 0.034, and 0.022, respectively).Conclusions: The present study revealed that stressful life events and mental health problems (i.e., depressive symptoms, poor sleep quality, and suicidal ideation) are predictors of problematic smartphone use in Chinese college students.

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Both smartphone addiction and phubbing are emerging behavioral problems. The present study investigates potential risk and protective factors of smartphone addiction and phubbing behavior, including demographic factors, personal factors, and interpersonal factors among Chinese college students. A total of 866 college students (Mage = 21.01, SD = 1.60) completed self-reported questionnaires in classroom settings. Collected data were analyzed by using Pearson’s correlation and hierarchical linear regression analyses. The risk factors for smartphone addiction were phubbing behavior, depression, and social anxiety, while the protective factors were self-control and sense of security. In addition, the risk factors for phubbing behavior included female sex and smartphone addiction, while the protective factors included sense of security and interpersonal adaptability. Our findings help to enhance understanding of the general and specific risks and protective factors for smartphone addiction and phubbing behavior, which can benefit intervention development for related behavior prevention and reduction.

Background This study aimed to categorize different subgroups of problematic smartphone use in Chinese college students. Differences in gender and psychosocial characteristics of the categorized groups were also examined. Methods A total of 1123 participants completed the Mobile Phone Addiction Index Scale, the Center for Epidemiologic Studies Depression Scale, the Perceived Social Support Scale, and the Perceived Stress Scale. Using latent profile analysis, we identified different subgroups of problematic smartphone use in college students. Multivariate logistic regression analysis was implemented to examine the relationship between latent classes and demographic and psychosocial covariates. Results The four following latent classes were identified: a low-risk group, a moderate-risk with no evasiveness group, a moderate-risk with evasiveness group, and high-risk group that accounted for 11%, 24.1%, 35.5%, and 29.4% of the total sample, respectively. Further analysis revealed that female participants were more likely to be in the moderate-risk with evasiveness and high-risk groups, and individuals with depressed mood were more likely to be in the moderate-risk and high-risk groups. Conclusions Classifying college students according to the features of problematic smartphone use is potentially useful for understanding risk factors and developing targeted prevention and intervention programs.